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Consultant (m,w,d) AD-Validation PM - SAE L4 Automated Driving & E2E AI Systems
P3 Group GmbH | online seit: 12.05.2026
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WHAT YOU'LL DO
- Lead and structure SAE Level 4 autonomous driving validation programs across the full development lifecycle, from concept phase to series readiness, homologation and operations
- Define and operationalize holistic validation strategies for E2E AI‑based AD systems, combining scenario‑based testing, data‑driven validation, simulation, and real‑world testing
- Translate regulatory, safety and quality requirements (ASPICE, ISO 26262, SOTIF, homologation, ISO PAS 8800) into executable validation concepts, KPIs and release criteria
- Analyze the validation implications of key AD system components, including camera, radar, lidar, sensor fusion, localization, prediction, planning, control, data pipelines and runtime monitoring
- Analyze / orchestrate SiL, HiL, MiL and vehicle‑level testing and ensure seamless integration into automated CI/CD pipelines
- Drive scalable validation approaches for AI models (incl. coverage metrics, corner‑case detection, data curation strategies, and confidence arguments)
- Define AI model validation KPIs and acceptance thresholds, including scenario coverage, ODD coverage, perception and planning performance, uncertainty calibration, robustness, latency, temporal consistency, rare-event behavior and regression stability
- Align validation scope and evidence with Type Approval and AD Safety Management Systems (AD‑SMS)
- Act as central interface between AI development teams, system engineers, toolchain providers, test organizations, and external stakeholders (e.g. authorities, partners, suppliers)
- Manage stakeholders at program and management level, including reporting, risk management, decision preparation and escalation
- Proactively identify validation risks related to AI behavior, operational design domain (ODD) boundaries, and system interactions
WHO YOU ARE
- A university degree in Engineering, Computer Science, Artificial Intelligence or a related field
- Solid understanding of AI/ML concepts for autonomous driving, including E2E vision-heavy approaches, data‑driven development and AI‑specific validation challenges
- Deep understanding of the validation challenges of SAE Level 4 automated driving systems, including ODD definition, scenario coverage, residual risk assessment, safety case development and evidence-based release decisions
- Hands‑on experience with Simulations, SiL and HiL testing, ideally integrated into automated CI/CD environments
- Strong technical understanding of AD system architectures, including modular pipelines, E2E AI models and hybrid architectures, as well as their impact on validation strategy and safety argumentation
- Practical knowledge of camera, radar and lidar sensor characteristics, sensor fusion principles, calibration, synchronization, degradation effects and typical failure modes relevant for AD validation
- Proven track record in high‑reliability industries (automotive, aerospace, medical), with deep exposure to ASPICE, ISO
26262, SOTIF and homologation processes - Strong analytical and structuring skills to translate abstract safety, regulatory and AI risks into concrete validation strategies
- Ability to work proactively and independently in agile, cross‑functional teams, lead validation initiatives, and align multiple internal and external stakeholders
Kontakt
P3 group GmbH
Daniel Wulf
D: +49 711 252 749 0
T: +497112527490
daniel.wulf@p3-group.com
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